BharadwajSarma's Stars
kaichunwu/MultithreadRestaurant
Restaurant Simulation
yousefkotp/Bug-Tracker
A bug tracking software which organizes the project between project managers and developers by tracking each bug within each project with a professional GUI and database.
harshilpatel1799/IoT-Network-Intrusion-Detection-and-Classification-using-Explainable-XAI-Machine-Learning
The continuing increase of Internet of Things (IoT) based networks have increased the need for Computer networks intrusion detection systems (IDSs). Over the last few years, IDSs for IoT networks have been increasing reliant on machine learning (ML) techniques, algorithms, and models as traditional cybersecurity approaches become less viable for IoT. IDSs that have developed and implemented using machine learning approaches are effective, and accurate in detecting networks attacks with high-performance capabilities. However, the acceptability and trust of these systems may have been hindered due to many of the ML implementations being ‘black boxes’ where human interpretability, transparency, explainability, and logic in prediction outputs is significantly unavailable. The UNSW-NB15 is an IoT-based network traffic data set with classifying normal activities and malicious attack behaviors. Using this dataset, three ML classifiers: Decision Trees, Multi-Layer Perceptrons, and XGBoost, were trained. The ML classifiers and corresponding algorithm for developing a network forensic system based on network flow identifiers and features that can track suspicious activities of botnets proved to be very high-performing based on model performance accuracies. Thereafter, established Explainable AI (XAI) techniques using Scikit-Learn, LIME, ELI5, and SHAP libraries allowed for visualizations of the decision-making frameworks for the three classifiers to increase explainability in classification prediction. The results determined XAI is both feasible and viable as cybersecurity experts and professionals have much to gain with the implementation of traditional ML systems paired with Explainable AI (XAI) techniques.
Mkhubaiib/Machine-Learning-Model-to-predict-attack-in-IOT-Devices
I developed a machine learning model for predicting SHA, DFA, SFA, SYA, and VNA attacks on IoT devices.
smuhabdullah/Sugarcane_project_3rd_Milestone
Final Year Project (Sugarcane disease detector)
RoshitaB/Sugarcane-Leaf-Disease-Detection
Transfer-Learning based Sugarcane Leaf Disease Detection Using DenseNet201 Architecture
rajvi-patel-22/Library-Management-System-Searching-catalogues-in-library-using-binary-search-tree
Our main objective in this project is to create a library management system wherein students can issue books and the admin or librarian can update/delete the record of books kept in the library. So we have the system into two parts : from user’s perspective and from admin’s perspective. First of all, the admin must login to handle the accounts where the username and password are already set. After he has logged in successfully, he can add, delete and update the books. He can add any new book in the already existing list of books. Similarly he can also delete any existing book. In the update option, the admin can update the quantity of books as well as the name of the book. As and when the admin adds the books, a binary search tree will be created where the nodes contain the name of books and are put in sorted order. Now if a student wants to issue/return any book, then he/she must login into the system, by enetering their valid university ID. The student will be allowed to issue/return only if their ID matches the list of university ID’s of students. When the student enters the name of book to be issued, that particular book will be searched by it’s name, in the already created binary search tree. If the book is not found in the tree, then a message will be printed “Book is not available in the library”. And if the book is out of stock, then this message will be printed, “This book is currently unavailable. Please try after some days.” Moreover, the student cannot issue more than 2 books simultaneously. When the student issues a book, the issuing date and time is recorded by the librarian. And if the student misses the due date of returning the book, then he has to pay that particular fine.
bbabina/Sorting-Visualizer
A pictorial representation demonstrating how Data Structures and Algorithms can be used to sort any data.
rohithaug/pathfinding-visualizer
Website built using React Framework for visualizing Pathfinding and Maze Generation Algorithms.
SurendraKumarKing/Weather-Predictor
Flood Prediction Web Application for Finland